Intern Researcher – Advanced Research (AI)

Communications House,, Staines-Upon-Thames, United Kingdom

Samsung Electronics

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Position Summary

We are currently looking for an intern to join us in the Advanced AI team here at Samsung Research UK. This will be a 6-9 month internship starting in October 2024. The R&D Centre is located in Staines-upon-Thames, Surrey, UK, and the role holder will be required to follow our hybrid policy of 3 days working onsite and 2 days working from home weekly.

The purpose of the role is to conduct cutting-edge mathematical and applied research on foundations and challenges of artificial intelligence (AI) to develop state-of-the-art solutions for real-world large-scale problems at Samsung Research and Development Institute, UK (SRUK). The research output will be disseminated in local and international research communities such as in research seminars, and top-tier conferences and journals.

The accepted interns will have the opportunity to work on diverse fields of AI as a member of the Advanced Research Team, including but not limited to machine learning, optimization theory, computer vision, pattern recognition, evolutionary computing, image and video processing, speech processing, natural language processing and understanding. In the application process, we’ll work with you to find the opportunity that best aligns with your interests and background.

During the internship, the interns are paired with mentors and expected to collaborate with other interns and research engineers. Interns at SRUK are encouraged and supported to contribute to local and international research communities and efforts by preparing high quality patent proposals and research papers (being listed as an author) with reproducible code for submission to top-tier conferences and journals.

Role and Responsibilities

  • Cutting-edge research to develop state-of-the-art solutions to existing problems and/or propose novel research challenges considering real-world case studies in AI.

  • Development of high quality code with detailed documentation to support reproducible research in local and international research communities in AI.

  • Publication in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, ACL, STOC, IEEE TPAMI, IEEE TNNLS, IEEE TSP, IEEE TIP, Information Fusion, JAIR, IJRR, IJCV, and JMLR.

Skills and Qualifications

  • Currently studying for a PhD in Computer Science, Engineering, Mathematics or a related discipline (or just completing).

  • Efficiency in elementary topics in mathematics (calculus, probability, statistics, linear algebra and optimization) and computer science (algorithms, data structures, parallel/distributed computing).

  • Experience in one or more general purpose programming languages including Python, Java, C and C++.

  • At least one first-author publication in one of the following conferences and journals: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, InterSpeech, EMNLP, ACL, STOC, COLT, AISTATS, UAI, MobiComm, IEEE TPAMI, IEEE TNNLS, IEEE TSP, IEEE TIP, IEEE IoT, Information Fusion, JAIR, IJRR, IJCV, and JMLR.

  • Experience and demonstrated output on Foundation Models research involving LLMs and/or Diffusion models.

Additional:

  • Experience in software libraries and toolboxes such as Tensorflow, PyTorch, SciKits, Kaldi, OpenCV and CUDA.

  • Experience in software engineering and development.

  • Relevant work experience as an intern or a researcher in an R&D Lab. in academy or industry.

  • Ability to design and execute a research agenda.

Contract Type: 6-9 month internship starting in October 2024

Job Location: Staines-upon-Thames, Surrey, UK

Hybrid Working: 3 days working from the office and 2 days working from home weekly.

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Tags: AIStats Computer Science Computer Vision CUDA Diffusion models EMNLP Engineering ICLR ICML Java JMLR Linear algebra LLMs Machine Learning Mathematics NeurIPS NLP OpenCV PhD Privacy Python PyTorch R R&D Research Statistics TensorFlow

Perks/benefits: Conferences

Region: Europe
Country: United Kingdom
Job stats:  54  9  0

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